{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import KBinsDiscretizer\n",
    "\n",
    "from feature_engine.wrappers import SklearnTransformerWrapper"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>MSSubClass</th>\n",
       "      <th>MSZoning</th>\n",
       "      <th>LotFrontage</th>\n",
       "      <th>LotArea</th>\n",
       "      <th>Street</th>\n",
       "      <th>Alley</th>\n",
       "      <th>LotShape</th>\n",
       "      <th>LandContour</th>\n",
       "      <th>Utilities</th>\n",
       "      <th>...</th>\n",
       "      <th>PoolArea</th>\n",
       "      <th>PoolQC</th>\n",
       "      <th>Fence</th>\n",
       "      <th>MiscFeature</th>\n",
       "      <th>MiscVal</th>\n",
       "      <th>MoSold</th>\n",
       "      <th>YrSold</th>\n",
       "      <th>SaleType</th>\n",
       "      <th>SaleCondition</th>\n",
       "      <th>SalePrice</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>65.0</td>\n",
       "      <td>8450</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>208500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "      <td>RL</td>\n",
       "      <td>80.0</td>\n",
       "      <td>9600</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2007</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>181500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>68.0</td>\n",
       "      <td>11250</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>223500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>70</td>\n",
       "      <td>RL</td>\n",
       "      <td>60.0</td>\n",
       "      <td>9550</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2006</td>\n",
       "      <td>WD</td>\n",
       "      <td>Abnorml</td>\n",
       "      <td>140000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>84.0</td>\n",
       "      <td>14260</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>250000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 81 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Id  MSSubClass MSZoning  LotFrontage  LotArea Street Alley LotShape  \\\n",
       "0   1          60       RL         65.0     8450   Pave   NaN      Reg   \n",
       "1   2          20       RL         80.0     9600   Pave   NaN      Reg   \n",
       "2   3          60       RL         68.0    11250   Pave   NaN      IR1   \n",
       "3   4          70       RL         60.0     9550   Pave   NaN      IR1   \n",
       "4   5          60       RL         84.0    14260   Pave   NaN      IR1   \n",
       "\n",
       "  LandContour Utilities  ... PoolArea PoolQC Fence MiscFeature MiscVal MoSold  \\\n",
       "0         Lvl    AllPub  ...        0    NaN   NaN         NaN       0      2   \n",
       "1         Lvl    AllPub  ...        0    NaN   NaN         NaN       0      5   \n",
       "2         Lvl    AllPub  ...        0    NaN   NaN         NaN       0      9   \n",
       "3         Lvl    AllPub  ...        0    NaN   NaN         NaN       0      2   \n",
       "4         Lvl    AllPub  ...        0    NaN   NaN         NaN       0     12   \n",
       "\n",
       "  YrSold  SaleType  SaleCondition  SalePrice  \n",
       "0   2008        WD         Normal     208500  \n",
       "1   2007        WD         Normal     181500  \n",
       "2   2008        WD         Normal     223500  \n",
       "3   2006        WD        Abnorml     140000  \n",
       "4   2008        WD         Normal     250000  \n",
       "\n",
       "[5 rows x 81 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# load house prices data set from Kaggle\n",
    "\n",
    "data = pd.read_csv('houseprice.csv')\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((1022, 79), (438, 79))"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# let's separate into training and testing set\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "    data.drop(['Id', 'SalePrice'], axis=1),\n",
    "    data['SalePrice'],\n",
    "    test_size=0.3,\n",
    "    random_state=0)\n",
    "\n",
    "X_train.shape, X_test.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['MSSubClass',\n",
       " 'LotFrontage',\n",
       " 'LotArea',\n",
       " 'OverallQual',\n",
       " 'OverallCond',\n",
       " 'YearBuilt',\n",
       " 'YearRemodAdd',\n",
       " 'MasVnrArea',\n",
       " 'BsmtFinSF1',\n",
       " 'BsmtFinSF2',\n",
       " 'BsmtUnfSF',\n",
       " 'TotalBsmtSF',\n",
       " '1stFlrSF',\n",
       " '2ndFlrSF',\n",
       " 'LowQualFinSF',\n",
       " 'GrLivArea',\n",
       " 'BsmtFullBath',\n",
       " 'BsmtHalfBath',\n",
       " 'FullBath',\n",
       " 'HalfBath',\n",
       " 'BedroomAbvGr',\n",
       " 'KitchenAbvGr',\n",
       " 'TotRmsAbvGrd',\n",
       " 'Fireplaces',\n",
       " 'GarageYrBlt',\n",
       " 'GarageCars',\n",
       " 'GarageArea',\n",
       " 'WoodDeckSF',\n",
       " 'OpenPorchSF',\n",
       " 'EnclosedPorch',\n",
       " '3SsnPorch',\n",
       " 'ScreenPorch',\n",
       " 'PoolArea',\n",
       " 'MiscVal',\n",
       " 'MoSold',\n",
       " 'YrSold']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cols = [var for var in X_train.columns if X_train[var].dtypes !='O']\n",
    "\n",
    "cols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 36 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X_train[cols].hist(bins=50, figsize=(15,15))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## KBinsDiscretizer\n",
    "\n",
    "### Equal-frequency discretization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GrLivArea     0.0\n",
       "GarageArea    0.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "variables = ['GrLivArea','GarageArea']\n",
    "\n",
    "X_train[variables].isnull().mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SklearnTransformerWrapper(transformer=KBinsDiscretizer(encode='ordinal'),\n",
       "                          variables=['GrLivArea', 'GarageArea'])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# at the moment it only works if the encoding in kbinsdiscretizer\n",
    "# is set to 'ordinal'\n",
    "\n",
    "discretizer = SklearnTransformerWrapper(\n",
    "    transformer = KBinsDiscretizer(\n",
    "        n_bins=5, strategy='quantile', encode='ordinal'),\n",
    "    variables = variables,\n",
    ")\n",
    "\n",
    "discretizer.fit(X_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['GrLivArea', 'GarageArea']"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "discretizer.variables_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KBinsDiscretizer(encode='ordinal')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "discretizer.transformer_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([array([ 334. , 1069.6, 1344. , 1603.2, 1893. , 4676. ]),\n",
       "       array([   0. ,  292.4,  438. ,  513. ,  618.6, 1356. ])],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# we can find the mean values within the parameters of the\n",
    "# simple imputer\n",
    "\n",
    "discretizer.transformer_.bin_edges_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# remove NA\n",
    "\n",
    "X_train = discretizer.transform(X_train)\n",
    "X_test = discretizer.transform(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.0    0.235160\n",
       "0.0    0.207763\n",
       "1.0    0.207763\n",
       "4.0    0.182648\n",
       "3.0    0.166667\n",
       "Name: GrLivArea, dtype: float64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_test['GrLivArea'].value_counts(normalize=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.0    0.212329\n",
       "4.0    0.205479\n",
       "2.0    0.203196\n",
       "0.0    0.189498\n",
       "1.0    0.189498\n",
       "Name: GarageArea, dtype: float64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_test['GarageArea'].value_counts(normalize=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAAEICAYAAACktLTqAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/Il7ecAAAACXBIWXMAAAsTAAALEwEAmpwYAAAUw0lEQVR4nO3de7BdZXnH8e9jAoKABASPmCDBiihKRecUtMzoGXGmQahQZRClEBw6aa0XrOlo7B/FzqADUylStGrqJbEGFW8TKtbWQU4tvaQStEZIVcRwyYSLSpCDWo0+/WOthJ3jPpe99jl7r7zn+5nZc/a6v3nz7N9Z591rrx2ZiSSpLI8bdgMkSXPPcJekAhnuklQgw12SCmS4S1KBDHdJKpDh3hIRMRERTx92OySVwXDvQ0ScFxGbIuLRiHigfv6nERFTrL8uIi7rtiwzD87MO3s49kURkRHx6qbtl6bSa20PW0S8s349nDLstrSF4d5QRKwGrgb+GngKMAL8CXAqsH+X9RfNcRNWAj8GLpyhnYvn+LgqXK+1PcO+5r3+6l84F+LrYW+Z6aPHB3Ao8CjwqmnWWQd8APhSve7L6nmXTbF+As8ATgHuAxZ1LPsD4Fsd08cAvwZeBewCntKxbAy4F3h7vZ9/oPolvgb4PvAj4Drg8I5tPlOv+zDwNeA5w+5jH8N5zLK2zwC+AfwEuAd4Z8ey5XUtXwzcDXytnj9ljQFPAv6x3t/XgcuAmzuWPwv4ClV4fwc4d1J7Xgz8DDi/ru/9O5ZdBPw7cFW97DLg8cB76vbdD3wQOLBe/zDgi8CDwEP182XD/n9p8vDMvZkXURXIxhnWey3wLuAQ4ObZ7DgzN1G9uF46aT/XdkxfCNySmZ8DtlIVdaenAIdT/RJYBbwJOBt4CfBUqqJ9f8f6/wQcBzwZuBXYMJu2qkizqe1HqWpwCVXQvz4izp60zkuAZwO/V09PV2Pvr/f5FKq/SFfuXhARB1EF+7X1tucBfxcRJ3Rsv5Lql8N19fTvT2rLKcCdVH+BvAu4HHgmcBLVCdVS4C/rdR8HfIzqtfM0ql8a75umL9pr2L9d9sUH8IfAfZPm/Qewk6oYXkx1lv7xSeusY4Yz9/r5ZcBH6+eHUBX+MR3rfg94S/38HcD/dCwbA34BHNAxbytwWsf0UcAvgcVd2rGkbsuhw+5nH4N/zKa2u2zzXuCq+vnyun6ePs0x9tQYsKiuxeM7lu85cwdeDfzbpO0/BFxaP38C1Rn/2R3LNnasexFwd8d01K+n3+qY9yLgB1O09STgoWH/vzR5eObezI+AIzrH7zLzdzNzSb1sd7/e03D/1wKvjIjHA68Ebs3MuwAi4lTgWOBTHeueGBEndWz/YGb+vGP6GOALEbEzInZShf2vgJGIWBQRl0fE9yPiJ8C2epsjGrZd+7YZazsiTomImyLiwYh4mGo8fnK97Kn9GWrsSGAxe79WOp8fA5yyu3br+j2f6iwfqiHLXVTDn1D9RXB6RBw5xf6OpPqFsLljf1+u5xMRT4iID0XEXXVbvwYsmYf3zOad4d7MfwL/B5w1w3qNbrmZmbcDdwGn85tDMiupzj6+GRH3AZs65k913HuA0zNzScfjgMzcXu//LKr3BA6lOvOiPoYWntnU9rXA9cDRmXko1Zj15HrprMHpauxBqnBe1rH+0R3P7wH+dVLtHpyZr6+XrwQOBu6uXw+fAfarj9mtLT+k+gvkOR37OzQzD66XrwaOB07JzCdS/RW+u637FMO9gczcCfwV1djfORFxSEQ8rj57PmiGzRdFxAEdj6muPrgWuISquD4DEBEHAOdSjaOf1PF4E/Daaa4E+CDwrog4pt7PkRGx+8V7CNWL+UdUZzTvnqH9Ktgsa/sQ4MeZ+fOIOJm9g7SbKWssM38FfB54Z33W/Cz2vuLli8AzI+KCiNivfvxORDw7IpYCpwFn8thr4XnAFUxx1Uxm/hr4e+CqiHgyQEQsjYjd7w0cQhX+OyPicODSGf5t7TXscaF9+UH15+F/Az+lOgPZRBW8+9NlfL2el5Meu8cW94y519NPo7oi5oaOeecBO4D9Ju33QKoXzpnUV8tMWv444K1UVxo8QnXVzLvrZQdTvXn2CNVfCxdObouPhfeYobbPqWvlEarwfR/wiXq75XX9LO7Y17Q1RjUkcgOPXS1zBXBjx/bH18sfrOv8q1RBvgbY3KXtT6Uax38u1Zj7zZOWH0D1C+bO+phbgTd3bDsOTADfBf548r9nX3lE/Q+SpFaIiCuoLu9dOePKmpLDMpKGKiKeFRG/HZWTqa6R/8Kw27WvWzif1pLUVocAn6QaErkfuJKZP0OiGTgsI0kFclhGkgrUimGZI444IpcvX9512aOPPspBB810dWH57IfKdP2wefPmH2bmkV0Xtow1PzP7odK05lsR7suXL+eWW27pumx8fJyxsbHBNqiF7IfKdP0QEXcNtjXNWfMzsx8qTWveYRlJKpDhLkkFMtwlqUCGuyQVyHCXpAIZ7pJUIMNdkgpkuEtSgQx3SSpQKz6hqplt2f4wF625oadttl1+xjy1RirL8h5fW9D+15dn7pJUIMNdkgo0Y7hHxEcj4oGI+HbHvMMj4isR8b3652H1/IiIv42IOyLiWxHxgvlsvCSpu9mcua8DVkyat4bqC2yPA26spwFOB46rH6uAD8xNMyVJvZgx3DPza8CPJ80+C1hfP18PnN0x/+NZ+S9gSUQcNUdtlSTNUtOrZUYyc0f9/D5gpH6+FLinY71763k7mCQiVlGd3TMyMsL4+HjXA01MTEy5bCEZORBWn7irp21K7DfrQfuyJlflrFvR7AtL+r4UMjMzInr+ItbMXAusBRgdHc2pbkbvDfsr12zYyJVbevvv2nb+2Pw0ZoisB2l2ml4tc//u4Zb65wP1/O3A0R3rLavnSZIGqOmZ+/XASuDy+ufGjvlvjIhPAacAD3cM30jSrPnBvf7MGO4R8UlgDDgiIu4FLqUK9esi4mLgLuDcevUvAS8H7gB+CrxuHtosSZrBjOGema+ZYtFpXdZN4A39NkqS1B8/oSpJBTLcJalAhrskFchwl6QCGe6SVCDDXZIKZLhLUoEMd0kqkOEuSQUy3CWpQH3f8lfS3BrUDbOa3Fu86bE0eJ65S1KBWn/m3uazGM9gJLWVZ+6SVCDDXepBRPxZRNwWEd+OiE9GxAERcWxEbIqIOyLi0xGx/7DbKRnu0ixFxFLgzcBoZj4XWAScB1wBXJWZzwAeAi4eXiuliuEu9WYxcGBELAaeAOwAXgp8tl6+Hjh7OE2THtP6N1SltsjM7RHxHuBu4GfAvwCbgZ2Zuate7V5gabftI2IVsApgZGSE8fHxrscZORBWn7ir67KpTLWv6fR6jH6O1cSg+gGa9cWg+nxiYqLRsQx3aZYi4jDgLOBYYCfwGWDFbLfPzLXAWoDR0dEcGxvrut41GzZy5ZbeXprbzu++r+n0ehVaP8dqYlD9AM36YlB9vm7FQUxVK9NxWEaavZcBP8jMBzPzl8DngVOBJfUwDcAyYPuwGijtZrhLs3c38MKIeEJEBNWXxN8O3AScU6+zEtg4pPZJexju0ixl5iaqN05vBbZQvX7WAm8H3hoRdwBPAj4ytEZKNcfcpR5k5qXApZNm3wmcPITmSFPyzF2SCmS4S1KBDHdJKpDhLkkFMtwlqUCGuyQVyHCXpAIZ7pJUoL7C3S8ukKR2ahzufnGBJLVXv8MyfnGBJLVQ43vL+MUFg/vSAhjsFxcMypbtD/e8zbGHLmr9v0tqg8bh7hcXDO5LC2CwX1wwKIP84gJpoelnWMYvLpCkluon3P3iAklqqcbh7hcXSFJ79fVlHX5xgSS1k59QlaQCGe6SVCDDXZIKZLhLUoEMd0kqkOEuSQUy3CWpQIa7JBWorw8xqTzLG9zMC2Db5WfMcUsk9cMzd0kqkOEuSQUy3CWpQIa7JBXIcJekAhnuklQgw12SCmS4S1KBDHdJKpDhLvUgIpZExGcj4n8jYmtEvCgiDo+Ir0TE9+qfhw27nZLhLvXmauDLmfks4HnAVmANcGNmHgfcWE9LQ2W4S7MUEYcCLwY+ApCZv8jMncBZwPp6tfXA2cNon9TJG4dJs3cs8CDwsYh4HrAZuAQYycwd9Tr3ASPdNo6IVcAqgJGREcbHx7seZORAWH3irp4aNtW+ptPrMfo5VhOD6gdo1heD6vOJiYlGxzLcpdlbDLwAeFNmboqIq5k0BJOZGRHZbePMXAusBRgdHc2xsbGuB7lmw0au3NLbS3Pb+d33NZ2Lmt4BtMGxmhhUP0CzvhhUn69bcRBT1cp0HJaRZu9e4N7M3FRPf5Yq7O+PiKMA6p8PDKl90h6GuzRLmXkfcE9EHF/POg24HbgeWFnPWwlsHELzpL04LCP15k3AhojYH7gTeB3VSdJ1EXExcBdw7hDbJwGGu9STzPwmMNpl0WkDboo0LYdlJKlAhrskFchwl6QCGe6SVKC+wt2bKElSO/V75u5NlCSphRqHuzdRkqT26uc69wV/E6VB3UAJ2t0PgzxW05soSQtNP+G+4G+iNKgbKEG7+2GQx2p6EyVpoelnzN2bKElSSzUOd2+iJEnt1e+9ZbyJkiS1UF/h7k2UJKmd/ISqJBXIcJekAhnuklQgw12SCmS4S1KBDHdJKpDhLkkFMtwlqUCGuyQVyHCXpAIZ7pJUIMNdkgpkuEtSgQx3SSqQ4S5JBTLcJalAhrskFchwl6QCGe6SVCDDXZIKZLhLUoEMd0kqkOEuSQUy3KUeRcSiiPhGRHyxnj42IjZFxB0R8emI2H/YbZQMd6l3lwBbO6avAK7KzGcADwEXD6VVUgfDXepBRCwDzgA+XE8H8FLgs/Uq64Gzh9I4qcPiYTdA2se8F3gbcEg9/SRgZ2buqqfvBZZ22zAiVgGrAEZGRhgfH+96gJEDYfWJu7oum8pU+5pOr8fo51hNDKofoFlfDKrPJyYmGh3LcJdmKSLOBB7IzM0RMdbr9pm5FlgLMDo6mmNj3XdxzYaNXLmlt5fmtvN7bg4Xrbmh522aHquJQfUDNOuLQfX5uhUHMVWtTMdwl2bvVOAVEfFy4ADgicDVwJKIWFyfvS8Dtg+xjRLgmLs0a5n5jsxclpnLgfOAr2bm+cBNwDn1aiuBjUNqorSH4S717+3AWyPiDqox+I8MuT1S/8MyEbEIuAXYnplnRsSxwKeoinwzcEFm/qLf40htkpnjwHj9/E7g5GG2R5psLs7cveZXklqmr3D3ml9Jaqd+h2XeywK+5ndQ1/tCu/thkMdqes2vtNA0Dnev+R3c9b7Q7n4Y5LGaXvMrLTT9nLl7za8ktVTjMXev+ZWk9pqP69y95leShmxObj/gNb+S1C5+QlWSCmS4S1KBDHdJKpDhLkkFMtwlqUCGuyQVyHCXpAIZ7pJUIMNdkgpkuEtSgQx3SSqQ4S5JBTLcJalAhrskFchwl6QCGe6SVCDDXZIKZLhLUoEMd0kqkOEuSQUy3CWpQIa7JBXIcJekAhnuklQgw12SCmS4S1KBDHdJKpDhLs1SRBwdETdFxO0RcVtEXFLPPzwivhIR36t/HjbstkqGuzR7u4DVmXkC8ELgDRFxArAGuDEzjwNurKeloTLcpVnKzB2ZeWv9/BFgK7AUOAtYX6+2Hjh7KA2UOiwedgOkfVFELAeeD2wCRjJzR73oPmBkim1WAasARkZGGB8f77rvkQNh9Ym7emrPVPuaTq/H6OdYTQyqH6BZXwyqzycmJhodq3G4R8TRwMepCjmBtZl5dUQcDnwaWA5sA87NzIeaHkdqm4g4GPgc8JbM/ElE7FmWmRkR2W27zFwLrAUYHR3NsbGxrvu/ZsNGrtzS20tz2/nd9zWdi9bc0PM2TY/VxKD6AZr1xaD6fN2Kg5iqVqbTz7CM449acCJiP6pg35CZn69n3x8RR9XLjwIeGFb7pN0ah7vjj1poojpF/wiwNTP/pmPR9cDK+vlKYOOg2yZNNidj7k3GH6V90KnABcCWiPhmPe8vgMuB6yLiYuAu4NzhNE96TN/h3nT8sYQ3lwb1xhK0ux8Geaymby7Nhcy8GYgpFp82yLZIM+kr3Kcbf8zMHdONP5bw5tKg3liCdvfDII/V9M0laaFpPObu+KMktVc/Z+6OP0pSSzUOd8cfJam9vP2AJBXIcJekAhnuklQgw12SCmS4S1KBDHdJKpDhLkkFMtwlqUCGuyQVyHCXpAIZ7pJUIMNdkgpkuEtSgQx3SSqQ4S5JBTLcJalAhrskFchwl6QCGe6SVCDDXZIKZLhLUoEMd0kqkOEuSQUy3CWpQIa7JBXIcJekAhnuklQgw12SCmS4S1KBDHdJKpDhLkkFMtwlqUDzEu4RsSIivhMRd0TEmvk4htQ21r3aZM7DPSIWAe8HTgdOAF4TESfM9XGkNrHu1TbzceZ+MnBHZt6Zmb8APgWcNQ/HkdrEulerRGbO7Q4jzgFWZOYf1dMXAKdk5hsnrbcKWFVPHg98Z4pdHgH8cE4buW+yHyrT9cMxmXnkIBuz22zq3prvmf1QaVTzi+evPdPLzLXA2pnWi4hbMnN0AE1qNfuhsi/3gzXfG/uh0rQf5mNYZjtwdMf0snqeVDLrXq0yH+H+deC4iDg2IvYHzgOun4fjSG1i3atV5nxYJjN3RcQbgX8GFgEfzczb+tjljH/GLhD2Q6WV/TDHdd/Kf+MQ2A+VRv0w52+oSpKGz0+oSlKBDHdJKlBrw92PckNEHB0RN0XE7RFxW0RcMuw2DVNELIqIb0TEF4fdlvlgzVes+701rftWhrsf5d5jF7A6M08AXgi8YYH2w26XAFuH3Yj5YM3vxbrfW6O6b2W440e5AcjMHZl5a/38Ear/4KXDbdVwRMQy4Azgw8Nuyzyx5mvW/WP6qfu2hvtS4J6O6XtZoP+5u0XEcuD5wKYhN2VY3gu8Dfj1kNsxX6z5Lqz75nXf1nBXh4g4GPgc8JbM/Mmw2zNoEXEm8EBmbh52WzQ41n1/dd/WcPej3LWI2I+qwDdk5ueH3Z4hORV4RURsoxqueGlEfGK4TZpz1nwH6x7os+5b+SGmiFgMfBc4jarAvw68ts9Puu5zIiKA9cCPM/MtQ25OK0TEGPDnmXnmkJsyp6z5x1j3v6lJ3bfyzD0zdwG7P8q9FbhuIRY51W/uC6h+Y3+zfrx82I3S3LPm92Ldz4FWnrlLkvrTyjN3SVJ/DHdJKpDhLkkFMtwlqUCGuyQVyHCXpAIZ7pJUoP8H0syZmDn5UMEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X_test[variables].hist()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "fenotebook",
   "language": "python",
   "name": "fenotebook"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.2"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
